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Markerless motion capture systems (MCS) have been developed as an alternative solution to overcome the limitations of 3D MCS as they provide a more practical and efficient setup process given, among other factors, the lack of sensors attached to the body. However, this might affect the accuracy of the measures recorded. Thus, this study is aimed at evaluating the level of agreement between a markerless MSC (i.e., MotionMetrix) and an optoelectronic MCS (i.e., Qualisys). For such purpose, 24 healthy young adults were assessed for walking (at 5 km/h) and running (at 10 and 15 km/h) in a single session. The parameters obtained from MotionMetrix and Qualisys were tested in terms of level of agreement. When walking at 5 km/h, the MotionMetrix system significantly underestimated the stance and swing phases, as well as the load and pre-swing phases ( p < 0.05) reporting also relatively low systematic bias (i.e., ≤ -0.03 s) and standard error of the estimate (SEE) (i.e., ≤0.02 s). The level of agreement between measurements was perfect (r > 0.9) for step length left and cadence and very large (r > 0.7) for step time left, gait cycle, and stride length. Regarding running at 10 km/h, bias and SEE analysis revealed significant differences for most of the variables except for stride time, rate and length, swing knee flexion for both legs, and thigh flexion left. The level of agreement between measurements was very large (r > 0.7) for stride time and rate, stride length, and vertical displacement. At 15 km/h, bias and SEE revealed significant differences for vertical displacement, landing knee flexion for both legs, stance knee flexion left, thigh flexion, and extension for both legs. The level of agreement between measurements in running at 15 km/h was almost perfect (r > 0.9) when comparing Qualisys and MotionMetrix parameters for stride time and rate, and stride length. The agreement between the two motion capture systems varied for different variables and speeds of locomotion, with some variables demonstrating high agreement while others showed poor agreement. Nonetheless, the findings presented here suggest that the MotionMetrix system is a promising option for sports practitioners and clinicians interested in measuring gait variables, particularly in the contexts examined in the study.

Background: Markerless systems to capture body motion require no markers to be attached to the body, thereby improving clinical feasibility and testing time. However, the lack of markers might affect the accuracy of measurements., Objective: This study aimed to determine the absolute reliability and concurrent validity of the Kinect system with MotionMetrix software for spatiotemporal variables during running at a comfortable velocity, by comparing data between the combination system and two widely used systems-OptoGait and high-speed video analysis at 1000 Hz., Methods: In total, 25 runners followed a running protocol on a treadmill at a speed of 12 km/h. The Kinect+MotionMetrix combination measured spatiotemporal parameters during running (ie, contact time, flight time, step frequency, and step length), which were compared to those obtained from two reference systems., Results: Regardless of the system, flight time had the highest coefficients of variation (OptoGait: 16.4%; video analysis: 17.3%; Kinect+MotionMetrix: 23.2%). The rest of the coefficients of variation reported were lower than 8.1%. Correlation analysis showed very high correlations (r>0.8; P<.001) and almost perfect associations (intraclass correlation coefficient>0.81) between systems for all the spatiotemporal parameters except contact time, which had lower values. Bland-Altman plots revealed smaller systematic biases and random errors for step frequency and step length and larger systematic biases and random errors for temporal parameters with the Kinect+MotionMetrix system as compared to OptoGait (difference: contact time +3.0%, flight time -7.9%) and high-speed video analysis at 1000 Hz (difference: contact time +4.2%, flight time -11.3%). Accordingly, heteroscedasticity was found between systems for temporal parameters (r 2 >0.1)., Conclusions: The results indicate that the Kinect+MotionMetrix combination slightly overestimates contact time and strongly underestimates flight time as compared to the OptoGait system and high-speed video analysis at 1000 Hz. However, it is a valid tool for measuring step frequency and step length when compared to reference systems. Future studies should determine the reliability of this system for determining temporal parameters., (©Felipe García-Pinillos, Diego Jaén-Carrillo, Victor Soto Hermoso, Pedro Latorre Román, Pedro Delgado, Cristian Martinez, Antonio Carton, Luis Roche Seruendo. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 23.10.2020.)

The main purpose of this study was to evaluate running kinematic characteristics and foot strike patterns (FSP) during early and late stages of actual and common high-intensity intermittent training (HIIT): 5 × 2000 m with 120-s recovery between runs. Thirteen healthy, elite, highly trained male endurance runners participated in this study. They each had a personal record in the half-marathon of 70 ± 2.24 min, and each had a minimum experience of 4 years of training and competition. Heart rate (HR) and rate of perceived exertion (RPE) were monitored during HIIT. High levels of exhaustion were reached by the athletes during HIIT (HRpeak: 174.30 bpm; RPE: 17.23). There was a significant increase of HRpeak and RPE during HIIT; nevertheless, time for each run remained unchanged. A within-protocol paired t-test (first vs. last run) revealed no significant changes (P ≥ 0.05) in kinematics variables and FSP variables during HIIT. There were no substantial changes on kinematics and FSP characteristics in endurance runners after fatigue induced by a HIIT. Only the minimum ankle alignment showed a significant change. The author suggests that these results might be due to both the high athletic level of participants and their experience in HIIT.

The aim of this study was to determine the influence of barefoot running on foot-strike patterns, eversion-inversion, running speed and vertical foot rotation in endurance runners. Eighty healthy recreational runners (age = 34.11 ± 12.95 years old, body mass index = 22.56 ± 2.65 kg · m(-2)) performed trials in shod/unshod running conditions on a treadmill at comfortable and competitive self-selected speeds. Data were collected by systematic observation of lateral and back recordings at 240 Hz. McNemar's test indicated significant differences between shod/unshod conditions and foot strike at comfortable and competitive speeds (P < 0.001). Speed was related to vertical foot rotation type for shod (P < 0.01) and unshod conditions (P < 0.05). Significant differences were found between shod/unshod conditions in foot rotation at comfortable running speeds (P < 0.001) and competitive running speeds (P < 0.01). No significant difference was found in inversion or eversion (P ≥ 0.05). In conclusion, the results suggest that running kinematics, in terms of foot-strike patterns and vertical foot rotation, differ between shod/unshod conditions, while the inversion or eversion degree remains unchanged.

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